University of Illinois

Richard Merle Weinshilboum

Liewei Wang

Ravishankar Krishnan Iyer

Mark Andrew Frye

Arjun Prasanna Athreya

William Victor Bobo

The present disclosure provides methods for accurately predicting the dynamics of symptom response to drugs or other interventions for the treatment of major depressive disorder or other psychological conditions. These methods can allow for a shortening of the time period necessary for the evaluation of a drug or other therapeutic intervention. These predictive methods are based on measured and/or self-reported symptom severity measures at two or more points in time. These measures are then discretized into symptom classes (e.g., low, moderate, severe) and the symptom classes are then applied to the predictive model to predict the progression of symptoms and/or the effectiveness of a drug or other therapeutic intervention. The predictive methods may be augmented by metabolomics data, genomics data, or other objective measures taken from a patient, allowing the use of objective physiological measures to diagnosis and treat psychological conditions heretofore diagnosed and assessed using only subjective, self-reported measures.

Growing community of inventors

Rochester, MN, United States of America

Richard Merle Weinshilboum